| # Deep Architecture Genealogy | |
| There are so many new models and architectures. If you find something interesting and worth paying attention to, please send us a pull requests (PR) and write issues. | |
| `README.md` is automatically generated. Please send PRs on the `Neural Net Arch Genealogy.txt` file. | |
| ## Mindmap Coggle Link | |
| https://coggle.it/diagram/Wf5mYoJbsgABUF9P | |
| ## Text Version | |
| This is automatically generated. Please send a PR on the `Neural Net Arch Genealogy.txt` file. | |
| * Reinforcement Learning Algorithms | |
| * A3C, '16.02.06 | |
| * DARLA, '17.07.26 | |
| * ACTKR, '17.08.17 | |
| * c51, '17.10.27 | |
| * CNN | |
| * AlexNet, '12.12 | |
| * VggNet, '14.09 | |
| * GoogLeNet, '14.09 | |
| * ResNet, '15.12 | |
| * DenseNet, '16.08 | |
| * SENet: Squeeze-and-Excitation Networks, '17.09 | |
| * Object Detection | |
| * R-CNN | |
| * Fast R-CNN | |
| * Faster R-CNN | |
| * Mask R-CNN | |
| * YOLO | |
| * SSD | |
| * R-FCN | |
| * Semantic Segmentation | |
| * FCN | |
| * DeconvNet | |
| * DeepLab | |
| * U-Net | |
| * Super-resolution | |
| * MemNet | |
| * FSRCNN | |
| * SRCNN | |
| * VDSR | |
| * DRCN | |
| * LabSRN | |
| * EDSR | |
| * TTS | |
| * Wavenet, '16.09.12 | |
| * Generative Models | |
| * Autoregressive models | |
| * MADE, '15.02.12 | |
| * PixelRNN, '16.01.25 | |
| * NADE, '16.05.07 | |
| * PixelCNN, '16.06.16 | |
| * PixelCNN++, '17.01.19 | |
| * Latent variable models | |
| * VAE, '13.12.20 | |
| * CVAE, '14.06.20 | |
| * AAE, '15.11.18 | |
| * AVB, '17.01.17 | |
| * VQ-VAE, '17.11.2 | |
| * GAN, '14.06.10 | |
| * Variants | |
| * CGAN, '14.11.06 | |
| * DCGAN, '15.11.19 | |
| * infoGAN, '16.06.12 | |
| * EBGAN, '16.09.11 | |
| * ACGAN, '16.10.30 | |
| * WGAN, '17.01.26 | |
| * BEGAN, '17.02.27 | |
| * WGAN-GP, '17.03.31 | |
| * TripleGAN, '17.03.07 | |
| * Applications | |
| * Pix2Pix, '16.11.21 | |
| * PPGN, '16.11.30 | |
| * StackGAN, '16.12.10 | |
| * RNN | |
| * LSTM, '97.11 | |
| * GRU, 14.11 | |
| * ACT: Adaptive Computation Time, '17.05 | |
| * S2S: RNN Encoder-Decoder, '14.06 | |
| * Attention: Jointly Learning to Align, '14.09 | |
| * Effective Approaches to Attention, Luong et al. '15.08 | |
| * DCN: Dynamic Coattention Networks, '16.08, DCN+, '17.08 | |
| * Transformer: Attention Is All You Need, '17.06 | |
| * Capsule Net, '17.10 | |
| * Memory Networks | |
| * Neural Programming | |
| * Neural Turing Machine,'14.10 | |
| * Neural Random-Access Machines,'16.02 | |
| * Hierarchical Attentive Memory, '16.02 | |
| * Neural GPUs Learn Algorithms, '16.03 | |
| * Neural Programmer,'16.08 | |
| * Neural Module Networks, '16.06 | |
| * Hybrid Computing, '16.10 | |
| * Memory Networks,'14.10 | |
| * End-to-End Memory Network,'15.03 | |
| * DMN: Dynamic Memory Network, '16.03, DMN+, '16.04 | |
| ## Contributions | |
| Your pull requests and issues are always welcome. |